Hierarchical Hybrid Modeling and Control of Cognitive Manufacturing Systems

In current manufacturing systems, short times for product development and ramp-up as well as high production rates and customized products are of increasing importance. To push the efficiency (and thus the economic gain) of produc- tion further, recent investigations combine aspects of flex ible manufacturing with technical cognition - the latter refers to a system's capability to perceive a momentary situation and t o pro-actively derive a production scheme that maximizes profit. Within this context, the contribution of this paper is two- fold: (1) a hierarchical modeling scheme is presented which is suitable to represent dynamics depending on a perceived situation, (2) an approach to adapt production online to changes in product specifications or production constraint s by combining high-level optimal plan generation with low-level learning- and model-based control. I. I NTRODUCTION